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Record W2328370506 · doi:10.1103/physreve.87.050302

One- and two-particle dynamics in microfluidic T-junctions

2013· article· en· W2328370506 on OpenAlexafffund
Santtu T. T. Ollila, Colin Denniston, Tapio Ala-Nissilä

Bibliographic record

VenuePhysical Review E · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsWestern University
FundersChina Scholarship CouncilCompute Canada
KeywordsStreamlines, streaklines, and pathlinesMicrofluidicsParticle (ecology)Materials scienceColloidal particlePhase diagramColloidPosition (finance)NanotechnologyPhase (matter)PhysicsMechanicsChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Advances in precise focusing of colloidal particles in microfluidic systems open up the possibility of using microfluidic junctions for particle separation and filtering applications. We present a comprehensive numerical study of the dynamics of solid and porous microparticles in T-shaped junctions. Good agreement with experimental data is obtained on the location of particle-separating streamlines for single solid particles with realistic parameters corresponding to the experiments. We quantify the changes in the position of the separating line for porous, partially penetrable colloids. A prediction of the full phase diagram for particle separation is presented in the case of two successive particles entering a T-junction. Our results suggest the intriguing possibility of using the one- and two-particle T-junctions as logic gates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.246
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2013
Admission routes2
Has abstractyes

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Same venuePhysical Review ESame topicMicrofluidic and Bio-sensing TechnologiesFrench-language works237,207